Method and apparatus for adjusting cardiac event detection threshold based on dynamic noise estimation

ABSTRACT

An implantable cardiac rhythm management (CRM) device includes a sensing and detection circuit that senses at least one cardiac signal and detects cardiac electrical events from the sensed estimation. The sensed cardiac signal is filtered to produce a filtered cardiac signal having a signal frequency band and a noise signal having a noise frequency band. The noise frequency band is substantially different from the signal frequency band. A dynamic noise floor is produced based on the noise signal and used as the minimum value for the detection threshold. A cardiac electrical is detected when the amplitude of the filtered cardiac signal exceeds the detection threshold.

CROSS REFERENCE TO RELATED APPLICATION(S)

This application is a division of U.S. patent application Ser. No.12/415,619, filed on Mar. 31, 2009, now issued as U.S. Pat. No.8,798,742, which is a continuation of U.S. patent application Ser. No.11/557,318, filed on Nov. 7, 2006, now issued as U.S. Pat. No.7,515,955, which is a continuation of U.S. patent application Ser. No.10/967,660, filed on Oct. 18, 2004, now issued as U.S. Pat. No7,155,275, the specifications of which are incorporated herein byreference.

FIELD OF THE INVENTION

This document generally relates to a cardiac rhythm management (CRM)systems and particularly, but not by way of limitation, to animplantable CRM device including a sensing and detection circuit thatdetects cardiac electrical events using a detection threshold that isadjusted based on dynamic noise estimation.

BACKGROUND

The heart is the center of a person's circulatory system. It includes anelectro-mechanical system performing two major pumping functions. Theleft portions of the heart draw oxygenated blood from the lungs and pumpit to the organs of the body to provide the organs with their metabolicneeds for oxygen. The right portions of the heart draw deoxygenatedblood from the organs and pump it into the lungs where the blood getsoxygenated. In a normal heart, the sinoatrial node, the heart's naturalpacemaker, generates electrical impulses, known as action potentials,that propagate through an electrical conduction system to variousregions of the heart to cause the depolarization of the electricalconduction system and excitation of myocardial tissues in these regions.Coordinated delays in the propagations of the electrical impulses in anormal electrical conduction system cause the various regions of theheart to contract in synchrony such that the pumping functions areperformed efficiently. Arrhythmia occurs, for example, when thesinoatrial node fails to generate the electrical impulses at a normalrate, when electrical impulses are generated from a pathological origin,and/or when pathological changes occur to the electrical conductionsystem. Arrhythmia causes the heart to contract at a rhythm that is tooslow, too fast, or irregular. Consequently, the heart's pumpingefficiency is reduced, and hence, the blood flow to the body isdiminished.

Implantable CRM devices are used to treat arrhythmias by deliveringelectrical pulses to the patient's heart. In one example, pacing pulsesare delivered to one or more regions of the heart to at least partiallyrestore the function of the sinoatrial node and/or the electricalconduction system. According to many pacing algorithms, a pacing pulseis delivered on demand, i.e., when a corresponding intrinsicdepolarization is absent or abnormally delayed. In another example, adefibrillation pulse is delivered to the heart to stop a rhythm that istoo fast and/or irregular. This requires detection of a depolarizationrate and/or pattern that warrant a delivery of the defibrillation pulse.Thus, the detection of cardiac electrical events includingdepolarizations is important in both pacing and defibrillationtherapies.

The cardiac depolarizations are detected from one or more cardiacsignals each sensed with at least one electrode placed in or on theheart. In addition to cardiac depolarizations, noises of various typesare often present in such cardiac signals. The sources of such noisesinclude, but not limited to, non-cardiac bioelectric activities such asmyoelectrical signals associated with breathing and/or bodily movementsand interference from nearby electrical power lines, equipment, andappliances. An implantable CRM device detects a cardiac depolarizationwhen the amplitude of a cardiac signal exceeds a detection threshold.When the threshold is set low, the noises may cause over-sensing, i.e.,the implantable CRM device detects noise as cardiac depolarizations.Consequently, the implantable CRM device fails to deliver pacing pulseswhen needed and/or delivers a defibrillation pulse that is not needed.When the threshold is set high to avoid detection of noise,under-sensing may occur, i.e., the implantable CRM device fails todetect cardiac depolarizations. Consequently, the implantable CRM devicedelivers of pacing pulses that are not needed or not properly timedbased to the heart's intrinsic activities and/or fails to deliver adefibrillation pulse when fibrillation occurs. Depending on the type oftherapy, over-sensing and under-sensing both have consequences rangingfrom inefficient therapy to death. For example, the consequence of afailure to deliver a defibrillation pulse may be fatal, while theconsequence of a delivering an unnecessary defibrillation pulse causessignificant discomfort to the patient and shortens the life expectancyof the implantable CRM device. For these and other reasons, there is aneed to provide an acceptably accurate detection of cardiac electricalevents in the presence of noise.

SUMMARY

An implantable CRM device includes a sensing and detection circuit thatsenses at least one cardiac signal and detects cardiac electrical eventsfrom the sensed cardiac signal using a detection threshold that isadjusted based on dynamic noise estimation. The sensed cardiac signal isfiltered to produce a filtered cardiac signal having a signal frequencyband and a noise signal having a noise frequency band. The noisefrequency band is substantially different from the signal frequencyband. A dynamic noise floor is produced based on the noise signal andused as the minimum value for the detection threshold. A cardiacelectrical is detected when the amplitude of the filtered cardiac signalexceeds the detection threshold.

In one embodiment, a cardiac sensing system includes a sensing circuit,a noise estimation circuit, and an event detection circuit. The sensingcircuit senses a cardiac signal and includes a signal filter to producea filtered cardiac signal based on the cardiac signal. The filteredcardiac signal has a signal frequency band. The noise estimation circuitincludes a noise filter and a noise floor generator. The noise filterproduces a noise signal based on the cardiac signal. The noise signalhas a noise frequency band that is substantially different from thesignal frequency band. The noise floor generator produces a dynamicnoise floor based on the noise signal. The event detection circuitincludes a threshold circuit and a comparator. The threshold circuitdynamically produces a detection threshold based on at least theamplitude of the filtered cardiac signal and the dynamic noise floor.The comparator compares the filtered cardiac signal to a detectionthreshold and indicates a detection of a cardiac electrical event whenthe amplitude of the filtered cardiac signal exceeds the detectionthreshold.

In one embodiment, an implantable CRM device includes one or moresensing channels, a therapy output circuit, and an implant controlcircuit, contained in an implantable housing. Each sensing channelsincludes a circuit of the cardiac sensing system. The therapy outputcircuit delivers one or more cardiac therapies. The implant controlcircuit controls the delivery of the one or more cardiac therapies inresponse to one or more cardiac electrical events detected by the one ormore sensing channels.

In one embodiment, a method for detecting cardiac electrical events isprovided. A cardiac signal is sensed. The cardiac signal is filtered toproduce a filtered cardiac signal for detecting the cardiac electricalevents in a signal frequency band and also filtered to produce a noisesignal for measuring a noise level in a noise frequency band. A dynamicnoise floor is produced based on the noise signal. A dynamic detectionthreshold is produced based on the amplitude of the filtered cardiacsignal and the dynamic noise floor. Cardiac electrical events aredetected by comparing the amplitude of the filtered cardiac signal tothe dynamic detection threshold.

This Summary is an overview of some of the teachings of the presentapplication and not intended to be an exclusive or exhaustive treatmentof the present subject matter. Further details about the present subjectmatter are found in the detailed description and appended claims. Otheraspects of the invention will be apparent to persons skilled in the artupon reading and understanding the following detailed description andviewing the drawings that form a part thereof, each of which are not tobe taken in a limiting sense. The scope of the present invention isdefined by the appended claims and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings, which are not necessarily drawn to scale, illustrategenerally, by way of example, but not by way of limitation, variousembodiments discussed in the present document.

FIG. 1 is an illustration of a CRM system including an implantablemedical device and portions of an environment in which the CRM systemoperates.

FIGS. 2-6 are graphs illustrating a concept for a cardiac eventdetection threshold that is noise-adaptive.

FIG. 2 is a graph illustrating a filtered cardiac signal having a signalfrequency band.

FIG. 3 is a graph illustrating a noise signal having a noise frequencyband within the signal frequency band.

FIG. 4 is a graph illustrating a noise level produced based on the noisesignal.

FIG. 5 is a graph illustrating a filtered noise level.

FIG. 6 is a graph illustrating the filtered cardiac signal, a dynamicnoise floor produced based on the filtered noise level, and the cardiacevent detection threshold dynamically adjusted based on the dynamicnoise floor.

FIG. 7 is a flow chart illustrating a method for cardiac sensing andevent detection using the cardiac event detection threshold.

FIG. 8 is a block diagram illustrating an embodiment of a cardiacsensing system.

FIG. 9 is a block diagram illustrating a specific embodiment of thecardiac sensing system.

FIG. 10 is a block diagram illustrating an embodiment of portions of acircuit of the implantable medical device including the cardiac sensingsystem.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings which form a part hereof, and in which is shown byway of illustration specific embodiments in which the invention may bepracticed. These embodiments are described in sufficient detail toenable those skilled in the art to practice the invention, and it is tobe understood that the embodiments may be combined, or that otherembodiments may be utilized and that structural, logical and electricalchanges may be made without departing from the spirit and scope of thepresent invention. The following detailed description provides examples,and the scope of the present invention is defined by the appended claimsand their equivalents.

It should be noted that references to “an”, “one”, or “various”embodiments in this disclosure are not necessarily to the sameembodiment, and such references contemplate more than one embodiment.

This document discusses, among other things, a method and system forsetting a minimum value for a dynamically adjustable detection thresholdused by an implantable CRM device to detect cardiac electrical eventsincluding depolarizations from a cardiac signal. The minimum value isalso dynamically adjustable based on an analysis of noise level in thecardiac signal. The CRM device senses the cardiac signal and filters thecardiac signal such that the cardiac electrical events are detected in apredetermined signal frequency band. A cardiac electrical event isdetected when the amplitude of the filtered cardiac signal exceeds thedynamically adjustable detection threshold. The dynamically adjustabledetection threshold is dynamically adjusted based on, for example, peakamplitudes detected from the filtered cardiac signal. A noise level inthe signal frequency band is estimated by measuring the noise level in anoise frequency band. The noise frequency band is a frequency rangewithin which the presence of signal energy is insignificant while thepresence of noise energy allows for an estimation of the noise level inthe signal frequency band. The estimated noise level, referred to as adynamic noise floor, is dynamically calculated for use as the minimumvalue of the dynamically adjustable detection threshold. This dynamicnoise floor prevents noise from being detected as cardiac electricalevents.

FIG. 1 is an illustration of a CRM system 100 and portions of anenvironment in which the CRM system 100 operates, CRM system 100includes an implantable medical device 110 that is electrically coupledto a heart 101 through a lead system 115. An external system 102communicates with implantable medical device 110 via a telemetry link105.

Implantable medical device 110 includes a hermetically sealed canhousing an electronic circuit. The hermetically sealed can alsofunctions as an electrode for sensing and/or pulse delivery purposes. Inone embodiment, as illustrated in FIG. 1, lead system 115 includes leads112 and 116. Implantable medical device 110 senses cardiac signals fromand delivers pacing and cardioversion/defibrillation pulses to heart101. Lead 112 is a pacing lead that includes a proximal end 113connected to implantable medical device 110 and a distal end 114disposed in the right atrium (RA) of heart 101. A pacing-sensingelectrode 120 is located at distal end 114. Another pacing-sensingelectrode 122 is located near distal end 114. Electrodes 120 and 122 areelectrically connected to implantable medical device 110 via separateconductors to allow sensing of an atrial electrogram and/or delivery ofatrial pacing pulses. Lead 116 is a defibrillation lead that includes aproximal end 117 connected to implantable medical device 110 and adistal end 118 disposed in the right ventricle (RV) of heart 101. Apacing-sensing electrode 124 is located at distal end 118. Adefibrillation electrode 126 is located near distal end 118 butelectrically separated from pacing-sensing electrode 124. Anotherdefibrillation electrode 128 is located at a distance from distal end118 for supraventricular placement. Electrodes 124, 126, and 128 areelectrically connected to implantable medical device 110 via separateconductors. Electrode 124 allows sensing of a ventricular electrogramand/or delivery of ventricular pacing pulses. Electrode 126 allowsdelivery of cardioversion/defibrillation pulses to a ventricular region.Electrode 128 allows delivery of cardioversion/defibrillation pulses toa supraventricular region.

Implantable medical device 110 includes a noise-adaptive sensing anddetection circuit 180, which includes one or more cardiac sensingsystems. Each cardiac sensing system senses a cardiac signal (such asthe atrial or ventricular electrogram) and detects cardiac electricalevents (such as atrial or ventricular depolarizations) from each sensedcardiac signal using a dynamically adjustable detection threshold. Toprevent over-sensing, the dynamically adjustable detection threshold ismade noise-adaptive by providing a dynamic noise floor. The dynamicnoise floor is based on a noise level dynamically estimated for thecardiac signal and provides for a minimum value for the dynamicallyadjustable detection threshold. Details of cardiac sensing circuit arediscussed below.

External system 102 allows for programming of implantable medical device110 and receives signals acquired by implantable medical device 110. Inone embodiment, external system 102 includes a programmer. In anotherembodiment, external system 102 is a patient management system includingan external device in proximity of implantable medical device 110, aremote device in a relatively distant location, and a telecommunicationnetwork linking the external device and the remote device. The patientmanagement system allows access to implantable medical device 110 from aremote location, for purposes such as monitoring patient status andadjusting therapies. In one embodiment, telemetry link 105 is aninductive telemetry link. In an alternative embodiment, telemetry link105 is a far-field radio-frequency telemetry link. Telemetry link 105provides for data transmission from implantable medical device 110 toexternal system 102. This may include, for example, transmittingreal-time physiological data acquired by implantable medical device 110,extracting physiological data acquired by and stored in implantablemedical device 110, extracting therapy history data stored inimplantable medical device 110, and extracting data indicating anoperational status of implantable medical device 100 (e.g., batterystatus and lead impedance). Telemetry link 105 also provides for datatransmission from external system 102 to implantable medical device 110.This may include, for example, programming implantable medical device110 to acquire physiological data, programming implantable medicaldevice 110 to deliver one or more therapies.

FIGS. 2-6 are graphs illustrating a concept for a noise-adaptive cardiacevent detection threshold. The graphs illustrate how the cardiac eventdetection threshold is established.

FIG. 2 is a graph illustrating a filtered cardiac signal 201. Filteredcardiac signal 201 is produced by filtering a sensed cardiac signal andhas a signal frequency band. Filtered cardiac signal 201 includescardiac electrical events 202 and a noise 203. In one embodiment,filtered cardiac signal 201 is an electrogram, and cardiac electricalevents 202 are cardiac depolarizations. In one specific embodiment,filtered cardiac signal 201 is a filtered atrial electrogram, andcardiac electrical events 202 are atrial depolarizations (P-waves). Inanother specific embodiment, filtered cardiac signal 201 is a filteredventricular electrogram, and cardiac electrical events 202 areventricular depolarizations (R-waves).

FIG. 3 is a graph illustrating a noise signal 301. Noise signal 301 isproduced by filtering the same sensed cardiac signal or filtered cardiacsignal 201 and has a noise frequency band. The noise frequency band ischosen to substantially suppress the cardiac electrical events whilesubstantially retaining the noise. Noise signal 301 includes cardiacelectrical events 302 and a noise 303. Cardiac electrical events 302correspond to cardiac electrical events 202 but have substantiallyattenuated amplitudes. Noise 303 corresponds to noise 203 andsubstantially retains its characteristics.

FIG. 4 is a graph illustrating a noise level 404 produced based on noisesignal 301. Noise level 404 is updated periodically to indicate theamplitude or energy level of noise signal 301. In one embodiment, noiselevel 404 is the root-mean-square value periodically calculated fromnoise signal 301. In another embodiment, noise level 404 is an estimateof the root-mean-square value periodically calculated from noise signal301. In one specific embodiment, noise level 404 is the rectifiedaverage of the amplitude of noise signal 301 calculated over successivepredetermined periods. The periods are sufficiently short such that thenoise level 404 is updated on a nearly continuous basis.

FIG. 5 is a graph illustrating a filtered noise level 504. In oneembodiment, noise level 404 is smoothed by a low-pass filter to producefiltered noise level 504. In one embodiment, noise level 404 is filteredwith a relative small time constant applied to rising edges and arelative large time constant applied to trailing edges.

FIG. 6 is a graph illustrating filtered cardiac signal 201, a dynamicnoise floor 605, and a cardiac event detection threshold 606. Dynamicnoise floor 605 is produced based on filtered noise level 504. In oneembodiment, dynamic noise floor 605 is produced by multiplying filterednoise level 504 with a coefficient or crest factor. In one embodiment,the coefficient is a constant empirically determined such that dynamicnoise floor 605 is above a substantial majority of noise peaksanticipated in filtered cardiac signal 201. In general, the coefficientis chosen for a clinically acceptable performance in noise rejection,i.e., a clinically acceptable probability of over-sensing and/or aclinically acceptable probability of under-sensing. Cardiac eventdetection threshold 606 is dynamically adjusted using the dynamic noisefloor as the minimum value. In one embodiment, a cardiac event detectionalgorithm is executed to produce a dynamically adjusted threshold.Cardiac event detection threshold 606 is set to that dynamicallyadjusted threshold if the dynamically adjusted threshold is higher thanthe dynamic noise floor and set to the dynamic noise floor if thedynamically adjusted threshold is not higher than the dynamic noisefloor.

In one embodiment, as illustrated in FIG. 6, cardiac event detectionthreshold. 606 is dynamically adjusted based on the peak amplitudes ofcardiac electrical events 202 and dynamic noise floor 605. Cardiac eventdetection threshold 606 tracks the amplitude of filtered cardiac signal201 when the amplitude of filtered cardiac signal 201 exceeds cardiacevent detection threshold 606 until the peak amplitude of each cardiacelectrical event 202 is reached. Cardiac event detection threshold 606stays at that peak amplitude and then decays exponentially in apiecewise linear manner until a minimum detection threshold is reached.A specific example fir detecting cardiac electrical events using such adynamically adjustable detection threshold is discussed in U.S. Pat. No.5,620,466, “DIGITAL AGC USING SEPARATE GAIN CONTROL AND THRESHOLDTEMPLATING,” U.S. Pat. No. 5,658,317, “THRESHOLD TEMPLATING FOR DIGITALAGC,” and U.S. Pat. No. 5,662,688, “SLOW GAIN CONTROL,” all assigned toCardiac Pacemakers, Inc., which are hereby incorporated by reference intheir entirety. Dynamic noise floor 605 provides for such a minimumdetection threshold. This embodiment illustrates by way of example, butnot by way of limitation, where the present subject matter isapplicable. It is to be understood that, in general, the present subjectmatter is applicable to all CRM devices that detect cardiac electricalevents using dynamically adjustable detection thresholds.

As illustrated in FIG. 6, an over-sensing event may occur at the onsetof noise 203 because there is a delay in adjusting dynamic noise floor605. That delay is due to the delay in updating noise level 404. Noiselevel 404 is updated at each end of the period during which the noiselevel is calculated from noise signal 301. A shorter period for thenoise level calculation, i.e., a higher frequency for adjusting dynamicnoise floor 605, further improves performance in noise rejection. Suchover-sensing occurs when there is a sudden and significant increase inthe noise amplitude, as illustrated in FIG. 6. An adequately determinedcoefficient or crest factor for producing dynamic noise floor 605prevents over-sensing when the noise amplitude changes more gradually.It is to be understood that over-sensing is clinically problematic onlywhen it happens too frequently. Therefore, the period for updating noiselevel 404 is determined such that the over-sensing associated with thedelay in updating noise level 404 is limited to a degree that isclinically acceptable. In general, parameters used in producing dynamicnoise floor 605, including the coefficient or crest factor formultiplying filtered noise level 504 and the period for updating noiselevel 404, are empirically determined, based on the nature of the noiseanticipated, such that the potential degree of over-sensing and/orunder-sensing are clinically acceptable.

The concept illustrated in FIGS. 2-6 is implemented by a process usingdigital and/or analog signal processing techniques. In one embodiment,the process is implemented using digital signal processing (DSP)technology. In another embodiment, the process includes analog signalprocessing. In another embodiment, the process includes combined analogand digital signal processing. For example, dynamic noise floor 605 isproduced from noise signal 301 using DSP, while the rest of the processis implemented by analog circuitry. Generally, DSP requires the smallestcircuit size and power consumption, which are important factors toconsider in the design of any battery-powered implantable medicaldevice.

In one specific embodiment, the cardiac signal is digitized atapproximately 400 samples per second before filtered cardiac signal 201and noise signal 301 are produced. The signal frequency band isapproximately 10-100 Hz. The noise frequency band is approximately50-100 Hz. Noise level 404 is calculated based on noise signal 301 aboutevery 160 milliseconds (or 64 samples of noise signal). Filtered noiselevel 504 is produced by filtering noise level 404 with a finite impulseresponse (FIR) filter.

FIG. 7 is a flow chart illustrating a method for cardiac sensing andevent detection using a dynamically adjustable cardiac event detectionthreshold such as cardiac event detection threshold 606 illustrated inFIG. 6. The method is discussed in detail below using digital signalprocessing as an example of implementation. However, those skilled inthe art will understand, upon reading and comprehending this document,that the method can also be implemented using analog signal processingor combined analog and digital signal processing.

A cardiac signal is sensed at 700. Examples of the cardiac signalincludes atrial and ventricular electrograms. The cardiac signal isdigitized by sampling at a predetermined sampling frequency. In oneembodiment, the sampling frequency is in a range between 200 and 1,000samples per second. In one specific embodiment, the sampling frequencyis approximately 400 samples per second. Before being digitized, thecardiac signal is filtered with an analog low-pass filter having acutoff frequency that is one half of the sampling frequency or lower.

The cardiac signal is filtered to produce a filtered cardiac signal at710. The filtered cardiac signal provides for detection the cardiacelectrical events in a signal frequency band. In one embodiment, inwhich the cardiac signal is an electrogram, the signal frequency bandhas a low cutoff frequency in a range between 1 Hz and 20 Hz and a highcutoff frequency in a range between 50 Hz and 200 Hz.

The cardiac signal is also filtered to produce a noise signal at 720.The noise signal provides for measurement of a noise level in a noisefrequency band. In one embodiment, the noise frequency band is withinthe signal frequency band and is substantially narrower than the signalfrequency band. The noise frequency band is chosen to allow anestimation of noise energy across the signal frequency band. In oneembodiment, the cardiac signal is directly filtered to produce the noisesignal. In another embodiment, the filtered cardiac signal having thesignal frequency band is filtered again to produce the noise signal. Inone embodiment, in which the cardiac signal is an electrogram, the noisefrequency band has a low cutoff frequency in a range between 40 Hz and60 Hz and a high cutoff frequency in a range between 70 Hz and 200 Hz.It is generally observed that in an electrogram having a signalfrequency band of approximately 10-100 Hz, the signal energy isconcentrated in the lower one half of the band while noise are typicallyevenly distributed throughout the band. Thus, in one embodiment, thenoise frequency band is chosen to be equal to approximately the upperone half of the signal frequency band.

A dynamic noise floor is produced based on the noise signal at 730. Thenoise signal is a digitized signal including noise samples each having anoise sample amplitude. In one embodiment, each noise sample amplitudeis set to a maximum amplitude if it exceeds that maximum amplitude. Thisavoids inclusion of large spurious deflections in the noise signal inthe process that produces the dynamic noise floor. The maximum amplitudeis dynamically determined based on the present dynamic noise floor. Inone specific embodiment, the maximum amplitude equals eight times thepresent dynamic noise floor. Then, a noise level is determined based onthe noise sample amplitudes of a predetermined number of successivenoise samples. In one specific embodiment, the noise level is an averagecalculated over every 64 successive noise samples. With the samplingfrequency of 400 samples per second, this updates the noise level every160 milliseconds. In one embodiment, the noise level is aroot-mean-square value calculated for the noise sample amplitudes of thepredetermined number of successive noise samples. In another embodiment,the noise level is an estimate of a root-mean-square value calculatedfor the noise sample amplitudes of the predetermined number ofsuccessive noise samples. In a specific embodiment, the noise sampleamplitudes are rectified, and the noise level is an average of therectified noise sample amplitudes calculated for the noise sampleamplitudes of the predetermined number of successive noise samples. Sucha rectified average provides a reasonable estimation of theroot-mean-square value for the purpose of producing the dynamic noisefloor. In one embodiment, the noise level is filtered with a low-passfilter such as an FIR filter. The filtered noise level is multiplied bya predetermined coefficient to produce the dynamic noise floor. Thecoefficient is empirically determined based on a desirable performancein noise rejection. The probability of over-sensing (detecting a noiseas a cardiac electrical event) is balanced against the probability ofunder-sensing (failing to detect a cardiac electrical event). Forexample, when cardiac electrical events are detected for controlling ananti-tachyarrhythmia therapy, the coefficient is experimentallydetermined to minimize the probability of over-sensing after firstminimizing the probability of under-sensing.

A dynamic detection threshold based on the amplitude of the filteredcardiac signal and the dynamic noise floor at 740. An initial detectionthreshold is produced based on at least the amplitude of the filteredcardiac signal. In one embodiment, peak amplitudes associated withcardiac electrical events in the filtered cardiac signal are detected.The initial detection threshold is produced based on at least the peakamplitudes. An specific example of producing such an initial detectionthreshold is discussed in U.S. Pat. Nos. 5,620,466, 5,658,317, and5,662,688, as cited above. The dynamic detection threshold is set to theinitial detection threshold when the initial detection threshold ishigher than the dynamic noise floor and to the dynamic noise floor whenthe initial detection threshold is not higher than the dynamic noisefloor.

The cardiac electrical events are detected using the dynamic detectionthreshold at 750. The detection of each cardiac electrical event isindicated when the amplitude of the cardiac signal exceeds the dynamicdetection threshold. In one embodiment, in which the cardiac signal isan electrogram, the cardiac electrical events include atrialdepolarizations (P-waves) and/or ventricular depolarizations (R-waves).

In one embodiment, the detection of cardiac electrical events isperformed for controlling a delivery of a cardiac therapy. In onespecific embodiment, a delivery of an anti-bradyarrhythmia therapy iscontrolled based on the outcome of detecting the cardiac electricalevents using the method discussed above with reference to FIG. 7. Inanother specific embodiment, a delivery of an anti-tachyarrhythmiatherapy is controlled based on the outcome of detecting the cardiacelectrical events using the method discussed above with reference toFIG. 7. In another specific embodiment, deliveries ofanti-bradyarrhythmia and anti-tachyarrhythmia therapies are concurrentlycontrolled based on the outcome of detecting the cardiac electricalevents using the method discussed above with reference to FIG. 7.

In one embodiment, in addition to detecting the cardiac electricalevents, a measure of noise presence in the cardiac signal, such as asignal-to-noise ratio (SNR), is calculated to serve as one parameterused for controlling the delivery of the cardiac therapy. In oneembodiment, a running average of the peak amplitudes associated withcardiac electrical events in the cardiac signal is calculated. An SNR isdynamically calculated as the ratio of the running average of the peakamplitudes to the dynamic noise floor. In a further embodiment, a lowSNR is indicated when the SNR is lower than a predetermined thresholdSNR. The low SNR serves as an alert signal for a particularly noisycardiac signal. In another further embodiment, a persistently low SNRwhen the SNR is lower than the predetermined threshold SNR for apredetermined period of time or a predetermined number of heart beats.

FIG. 8 is a block diagram illustrating an embodiment of a cardiacsensing system 830. Cardiac sensing system 830 is one embodiment of thecardiac sensing system of noise-adaptive sensing and detection circuit180 and includes a sensing circuit 840, a noise estimation circuit 850,and an event detection circuit 860. In one embodiment, noise-adaptivesensing and detection circuit 180 includes a plurality of cardiacsensing channels each including a circuit of cardiac sensing system 830as illustrated in FIG. 8.

Sensing circuit 840 senses a cardiac signal such as an electrogram.Sensing circuit 840 receives the cardiac signal from electrodes placedin or on the heart and includes a signal filter 848 to filter thecardiac signal. Signal filter 848 produces a filtered cardiac signalhaving a signal frequency band.

Noise estimation circuit 850 includes a noise filter 852 and a noisefloor generator 858. Noise filter 852 produces a noise signal based onthe cardiac signal. The noise signal has a noise frequency band that issubstantially different from the signal frequency band. Noise floorgenerator 858 produces a dynamic noise floor based on the noise signal.

Event detector 860 includes a comparator 862 and a threshold circuit864. Comparator 862 has a first input to receive the filtered cardiacsignal, a second input to receive a detection threshold, and an outputto indicate a detection of a cardiac electrical event when the signalamplitude exceeds the detection threshold. Threshold circuit 864dynamically produces the detection threshold based on at least thefiltered cardiac signal and the dynamic noise floor.

In one embodiment, cardiac sensing system 830 is a substantially analogcircuit. In another embodiment, cardiac sensing system 830 is asubstantially digital circuit. In one specific embodiment, sensingcircuit 840 digitizes the cardiac signal before feeding it to signalfilter 848 and noise filter 852. This allows signal filter 848, noiseestimation circuit 850, and event detection circuit 860 to beimplemented by DSP technology.

FIG. 9 is a block diagram illustrating a cardiac sensing system 930,which is a specific embodiment of cardiac sensing system 830. Cardiacsensing system 930 includes a sensing circuit 940, a noise estimationcircuit 950, an event detection circuit 960, and an SNR monitoringcircuit 970. As illustrated in FIG. 9, cardiac sensing system 930 isimplemented using substantially digital circuitry. However, thoseskilled in the art will understand, upon reading and comprehending thisdocument, that cardiac sensing system 930 can also be implemented usingsubstantially analog circuitry or combined analog and digital circuitry.

As a specific embodiment of sensing circuit 840, sensing circuit 940senses a cardiac signal and includes a sensing amplifier 942, ananalog-to-digital converter (ADC) 944, and a signal filter 948. Sensingamplifier 942 receives the cardiac signal through electrodes such asintracardiac or epicardial electrodes and amplifies the cardiac signal.In one embodiment, sensing amplifier 942 also includes an analogband-pass filter to filter the cardiac signal before its digitization.ADC 944 digitizes the cardiac signal by sampling it at a predeterminedsampling frequency. In one embodiment, the sampling frequency is in therange between 200 and 1,000 samples per second. In one specific example,the sample rate is approximately 400 samples per second. Signal filter948 produces a filtered cardiac signal by filtering the digitizedcardiac signal. Signal filter 948 is a band-pass filter having a lowcutoff frequency and a high cutoff frequency. In one embodiment, signalfilter 948 has a low cutoff frequency in a range between 1 Hz and 20 Hzand a high cutoff frequency in a range between 50 Hz and 200 Hz. In onespecific embodiment, in which the cardiac signal is an electrogram,signal filter 948 has a low cutoff frequency of approximately 10 Hz anda high cutoff frequency of approximately 100 Hz. The filtered cardiacsignal has a signal frequency band dependent on the cutoff frequenciesof signal filter 948.

Noise estimation circuit 950 is a specific embodiment of noiseestimation circuit 850 and includes a noise filter 952, a sample maximumlimiter 954, a noise level calculator 956, and a noise floor generator958. Noise filter 952 produces a noise signal having a noise frequency.In one embodiment, the noise frequency band is within the signalfrequency band and substantially narrower than the signal frequencyband. In one embodiment, as illustrated in FIG. 9, noise filter 952 is ahigh-pass filter that receives the filtered cardiac signal and producesthe noise signal by further filtering the filtered cardiac signal. Inone embodiment, noise filter 952 (high-pass filter) has a cutofffrequency in a range between 40 Hz and 60 Hz. In one specificembodiment, in which the cardiac signal is an electrogram and signalfilter 948 has a low cutoff frequency of approximately 10 Hz and a highcutoff frequency of approximately 100 Hz, noise filter 952 (high-passfilter) has a cutoff frequency of approximately 50 Hz. In an alternativeembodiment, noise filter 952 is a band-pass filter that receives thedigitized cardiac signal and produces the noise signal by filtering thedigitized cardiac signal. In one embodiment, noise filter 952 (band-passfilter) has a low cutoff frequency in a range between 40 Hz and 60 Hzand a high cutoff frequency in a range between 50 Hz and 200 Hz. In onespecific embodiment, in which the cardiac signal is an electrogram andsignal filter 948 has a low cutoff frequency of approximately 10 Hz anda high cutoff frequency of approximately 100 Hz, noise filter 952(band-pass filter) has a low cutoff frequency of approximately 50 Hz anda high cutoff frequency of approximately 100 Hz. The noise signal is adigitized signal including noise samples each having a noise sampleamplitude.

Sample maximum limiter 954 sets each noise sample amplitude to a maximumamplitude if that noise sample amplitudes exceeds the maximum amplitude.In one embodiment, sample maximum limiter 954 includes a maximumamplitude calculator to dynamically calculate the maximum amplitudebased on the dynamic noise floor. In one specific embodiment, themaximum amplitude calculator dynamically sets the maximum amplitude toeight times the dynamic noise floor.

Noise level calculator 956 calculates a noise level based on the noiseamplitudes of a predetermined number of successive noise samples. In oneembodiment, in which. ADC 944 digitizes the cardiac signal at thesampling frequency of 400 samples per second, noise level calculator 956calculates the noise level based on the noise sample amplitudes of 64successive noise samples. That is, noise level calculator 956 calculatesthe noise level based on the noise sample amplitudes measured over 160milliseconds (64 samples/400 samples per second). In one embodiment, thenoise level is the root-mean-square value for the noise sampleamplitudes of the predetermined number of successive noise samples.Noise level calculator 956 includes a root-mean-square value calculatorto calculate the noise level. In another embodiment, the noise level isan estimate of the root-mean-square value for the noise sampleamplitudes of the predetermined number of successive noise samples. Thisprovides a way to reduce circuit size and power consumption associatedto the computation of the root-mean-square value. Noise level calculator956 includes a root-mean-square value estimator to calculate the noiselevel. In one specific embodiment, a rectified average is calculated asthe estimate of the root-mean-square value. Noise level calculator 956includes a rectifier and an average calculator. The rectifier rectifiesthe noise sample amplitudes. The average calculator calculates theaverage of the rectified noise sample amplitudes for the noise sampleamplitudes of the predetermined number of successive noise samples.

Noise floor generator 958 generates the dynamic noise floor based on thecalculated noise level. The noise floor is an estimate of the noiselevel in the signal frequency band calculated based on the noise levelcalculated for the noise frequency band. In one embodiment, noise floorgenerator 958 includes a low-pass filter to smooth the calculated noiselevel and a noise level converter to produce the dynamic noise floor byconverting the noise level for the noise frequency band to an estimateof the noise level for the signal frequency band. In one specificembodiment, the low-pass filter includes an FIR filter, and the noiselevel converter produces the dynamic noise floor by multiplying thefiltered noise level with a predetermined coefficient. The coefficientis empirically determined and programmed into cardiac sensing system930.

Event detector 960 is a specific embodiment of event detection circuit860 and includes a comparator 962 and a threshold circuit 964.Comparator 962 has a first input to receive the filtered cardiac signal,a second input to receive a detection threshold, and an output toindicate a detection of a cardiac electrical event when the amplitude ofthe filtered cardiac signal exceeds the detection threshold. Thresholdcircuit 964 includes an initial threshold calculator 966 and a thresholdgenerator 968. Initial threshold calculator 966 produces an initialdetection threshold based on at least the amplitude of the filteredcardiac signal and the dynamic noise floor. In one embodiment, initialthreshold calculator 966 includes a peak measurement circuit thatmeasures peak amplitudes from the filtered cardiac signal. The peakamplitudes are each an amplitude measured at the peak of a detectedcardiac electrical event. Initial threshold calculator 966 sets theinitial detection threshold based on at least the peak amplitudes. Oneexample of setting a cardiac event detection threshold based on peakamplitudes of a cardiac signal is discussed in U.S. Pat. Nos. 5,620,466,5,658,317, and 5,662,688, as cited above. Threshold generator 968 setsthe detection threshold to the initial detection threshold when theinitial detection threshold is higher than the dynamic noise floor, andto the dynamic noise floor when the initial detection threshold is nothigher than the dynamic noise floor.

SNR measurement circuit 970 includes an SNR calculator 972, a low-SNRdetector 974, a persistent low-SNR detector 976, and a timer 978. SNRcalculator 972 dynamically calculates an SNR indicative of the degree ofpresence of noise in the cardiac signal. In one embodiment, SNRcalculator 972 includes a signal amplitude average calculator tocalculate a running average of the peak amplitudes measured from thefiltered cardiac signal. SNR calculator 972 dynamically calculates theSNR as the ratio of the running average of the peak amplitudes to thedynamic noise floor. Low-SNR detector 974 includes an SNR comparatorhaving a first input to receive the SNR, a second input to receive apredetermined threshold SNR, and an output to indicate a low SNR whenthe SNR is lower than the predetermined threshold SNR. After a low SNRis detected, persistent low-SNR detector 976 detects a persistently lowSNR. In one embodiment, tinier 978 starts timing in response to anindication of the low SNR. If the output of low-SNR detector 974indicates the low SNR for at least a predetermined period of time astimed by timer 978, persistent low-SNR detector 976 indicates adetection of persistently low SNR. In one specific embodiment, timer 978includes a counter. The counter starts counting heart beats in responseto an indication of the low SNR. If the output of low-SNR detector 974indicates the low SNR for at least a predetermined number of heart beatsas counted by the counter, persistent low-SNR detector 976 indicates adetection of persistently low SNR.

FIG. 10 is a block diagram illustrating an embodiment of portions of acircuit of an implantable medical device 1010. As an exemplaryembodiment of implantable medical device 110 discussed for illustrativebut not restrictive purposes, implantable medical device 1010 is animplantable cardioverter/defibrillator (ICD) with cardiac pacingcapabilities, i.e., a combined pacemaker and cardioverter/defibrillator.

Implantable medical device 1010 includes hermetically sealed can 1095that houses a circuit including a noise-adaptive sensing and detectioncircuit 1080, a therapy output circuit 1084, an implant controller 1090,and an implant telemetry module 1096. The circuit is powered by abattery that is also housed in can 1095. Implant telemetry module 1096provides implantable medical device 1010 with the capability ofcommunicating with an external device or system such as external system102 via telemetry link 105.

Noise-Adaptive sensing and detection circuit 1080 is one embodiment ofnoise-adaptive sensing and detection circuit 180 and includes one ormore sensing channels 1082 each including cardiac sensing system 830 (or930 as a specific embodiment). Each sensing channel 1082 is used tosense one electrogram from the heart and detect depolarizations form thesensed electrogram. Therapy output circuit 1084 includes a pacingcircuit 1086 to deliver pacing pulses to the heart and acardioversion/defibrillation circuit 1088 to delivercardioversion/defibrillation pulses to the heart. Noise-Adaptive sensingand detection circuit 1080 and therapy output circuit 1084 areelectrically coupled to the heart through a lead system 1015. Leadsystem 1015 includes a plurality of electrodes placed in and/or on theheart. One example of lead system 1015 is lead system 115.

Implant control circuit 1090 includes a pacing controller 1092 and acardioversion/defibrillation 1094. Pacing controller 1092 controls thedelivery of the pacing pulses, and cardioversion/defibrillationcontroller 1094 controls the delivery of thecardioversion/defibrillation pulses, based on the detected cardiacdepolarizations. Cardiac sensing system 830 allows the cardiacdepolarizations to be detected using the same detection circuitconfiguration for use in the control of both pacing andcardioversion/defibrillation deliveries. In other words, sensingchannels 1082 are a plurality of substantially identical circuits eventhough one or more channels detect depolarizations for pacing controller1092 and another one or more channels detect depolarizations forcardioversion/defibrillation 1094.

Noise in a cardiac signal such as an electrogram potentially causesdifferent problems in anti-bradyarrhythmia therapy andanti-tachyarrhythmia therapy. One example is that myoelectric signalsassociated with diaphragmatic contractions may be sensed by a cardiacsensing circuit. If the diaphragm contractions are detected as cardiacdepolarizations, anti-bradyarrhythmia pacing may be erroneouslyinhibited, causing dizziness in the patient, or a defibrillation pulsemay be erroneously delivered, causing unnecessary pain in the patientand shortening an ICD's life expectancy. Because such diaphragmcontractions may have amplitudes similar to that of cardiacdepolarizations when seen in an electrogram, increasing the detectionthreshold may cause under-sensing. Such under-sensing may causeunsynchronized pacing that reduces the effectiveness ofanti-bradyarrhythmia pacing and/or erroneous inhibition of the deliveryof a defibrillation pulse, which is life-threatening. Because thepresence of noise in an electrogram is expected, different detectionstrategies have been applied to detect cardiac depolarization dependingon the purpose, i.e., whether the cardiac depolarizations are detectedfor controlling pacing or cardioversion/defibrillation. To ensurepatient safety, a known strategy is to set the detection threshold witha bias toward under-sensing for control of anti-bradyarrhythmia pacingand to set the detection threshold to with a bias toward over-sensingfor control of cardioversion/defibrillation. However, this not onlyrequires different circuits and/or different programming procedures, butalso causes sub-optimal pacing therapy and/or unnecessary delivery ofcardioversion/defibrillation energy. Because the noise is the cause ofthe problem, and the level of noise presence in a cardiac signal changesover time, using the dynamic noise floor as discussed in this documentprovides for a performance in cardiac electrical event detection that isrelatively independent of the noise. The use of the dynamic noise flooralso provides for a circuit configuration that is suitable for detectingcardiac electrical events in both pacing andcardioversion/defibrillation therapies. In one embodiment, cardiacsensing system 830 is used as the basic circuit configuration fordetection of cardiac electrical events for both anti-bradyarrhythmiapacing control and cardioversion/defibrillation control purposes.

While the present subject matter is described above using itsapplication in an implantable CRM device as an example, it is to beunderstood that it is generally applicable in implantable ornon-implantable, cardiac or non-cardiac medical devices and systems. Thepresent subject matter provides for a method and system for setting adynamic minimum value for a dynamically adjustable detection thresholdused to detect events from a signal sensed by a medical device toindicate biological activities. The medical device senses the signal andfilters the signal such that the events are detected in a predeterminedsignal frequency band. An event is detected when the amplitude of thesignal exceeds the dynamically adjustable detection threshold. The noiselevel in the signal frequency band is estimated by measuring the noiseenergy in a noise frequency band. The noise frequency band is selectedfrom a frequency range within which the presence of signal energy isinsignificant while the noise level can be measured to serve as thebasis for estimating the noise level in the signal frequency band. Thisdynamically estimated noise level is used as the minimum value for thedynamically adjustable detection threshold to prevent noise from beingdetected as the events.

It is to be understood that the above detailed description is intendedto be illustrative, and not restrictive. Other embodiments, includingany possible permutation of the system components discussed in thisdocument, will be apparent to those of skill in the art upon reading andunderstanding the above description. The scope of the invention should,therefore, be determined with reference to the appended claims, alongwith the full scope of equivalents to which such claims are entitled.

What is claimed is:
 1. A method for operating an implantable medicaldevice, the method comprising: sensing a cardiac signal; producing afiltered cardiac signal having a signal frequency band by filtering thesensed cardiac signal; producing a noise signal having a noise frequencyband by filtering the sensed cardiac signal or the filtered cardiacsignal, the noise frequency band being substantially different from thesignal frequency band; producing a dynamic noise floor being a dynamicestimate of noise level in the signal frequency band using the noisesignal; producing a detection threshold using the filtered cardiacsignal and the noise floor, the noise floor used as a minimum value ofthe detection threshold; and detecting cardiac electrical events usingthe filtered cardiac signal and the detection threshold.
 2. The methodof claim 1, wherein sensing the cardiac signal comprises sensing anelectrogram, and detecting the cardiac electrical events comprisesdetecting cardiac depolarizations.
 3. The method of claim 1, whereinproducing the detection threshold comprises: producing an initialdetection threshold using at least amplitude of the filtered cardiacsignal; and producing the detection threshold by dynamically adjustingthe initial detection threshold using the dynamic noise floor as aminimum value of the detection threshold.
 4. The method of claim 3,wherein producing the dynamic noise floor comprises: choosing the noisefrequency hand for allowing for estimation of the noise level in thesignal frequency band; and measuring a noise level in the noisefrequency band.
 5. The method of claim 4, wherein the noise frequencyband is within and substantially narrower than the signal frequencyband.
 6. The method of claim 5, wherein sensing the cardiac signalcomprises sensing an electrogram, and choosing the noise frequency bandcomprises choosing a frequency band equal to approximately an upper onehalf of the signal frequency hand as the noise frequency band.
 7. Themethod of claim 5, wherein producing the dynamic noise floor comprises:calculating a noise level for the noise frequency band using the noisesignal; and generating the noise floor using the noise level calculatedfor the noise frequency band.
 8. The method of claim 7, whereinproducing the dynamic noise floor comprises: filtering the calculatednoise level using a finite impulse response (FIR) filter; andmultiplying the filtered noise level with a coefficient.
 9. The methodof claim 1, comprising: measuring peak amplitudes of the filteredcardiac signal; calculating a running average of the peak amplitudes;calculating a dynamic signal-to-noise ratio (SNR) being a ratio of therunning average of the peak amplitudes to the noise floor; and detectinglow SNR using the dynamic SNR and a threshold SNR.
 10. The method ofclaim 9, comprising: starting a predetermined period in response to adetection of the low SNR, the predetermined period measured by time ornumber of heart beats; and indicating a persistently low SNR in responseto the dynamic SNR being lower than the threshold SNR for thepredetermined period.
 11. The method of claim 1, wherein sensing thecardiac signal, producing the filtered cardiac signal, producing thedynamic noise floor, producing the detection threshold, and detectingthe cardiac electrical events comprises sensing the cardiac signal,producing the filtered cardiac signal, producing the dynamic noisefloor, producing the detection threshold, and detecting the cardiacelectrical events using the implantable medical device.
 12. The methodof claim 11, wherein producing the detection threshold comprisesdynamically adjusting the detection threshold using the noise floor as aminimum value of the detection threshold.
 13. The method of claim 12,wherein producing the filtered cardiac signal comprises filtering thesensed cardiac signal using a signal frequency band-pass filter, andproducing the noise signal comprises filtering the sensed cardiac signalusing a noise frequency hand-pass filter.
 14. The method of claim 13,wherein filtering the sensed cardiac signal using the signal frequencyband-pass filter comprises filtering the sensed cardiac signal using afirst band-pass filter having a first low cutoff frequency in a rangebetween 1 Hz and 20 Hz and a first high cutoff frequency in a rangebetween 50 Hz and 200 Hz, and filtering the sensed cardiac signal usingthe noise frequency band-pass filter comprises filtering the sensedcardiac signal using a second band-pass filter having a second lowcutoff frequency in a range between 40 Hz and 60 Hz and a second highcutoff frequency in a range between 50 Hz and 200 Hz.
 15. The method ofclaim 14, wherein the first low cutoff frequency is approximately 10 Hz,the first high cutoff frequency is approximately 100 Hz, the second lowcutoff frequency is approximately 50 Hz, and the second high cutofffrequency is approximately 100 Hz.
 16. The method of claim 12, whereinproducing the filtered cardiac signal comprises filtering the sensedcardiac signal using a band-pass filter, and producing the noise signalcomprises filtering the filtered cardiac signal using a high-passfilter.
 17. The method of claim 16, wherein filtering the sensed cardiacsignal using the band-pass filter comprises filtering the sensed cardiacsignal using a first band-pass filter having a first low cutofffrequency in a range between 1 Hz and 2.0 Hz and a first high cutofffrequency in a range between 50 Hz and 200 Hz, and filtering thefiltered cardiac signal using the high-pass filter comprises filteringthe filtered cardiac signal using a second high-pass filter having asecond low cutoff frequency in a range between 40 Hz and 60 Hz.
 18. Themethod of claim 17, wherein the first low cutoff frequency isapproximately 10 Hz, the first high cutoff frequency is approximately100 Hz, and the second low cutoff frequency is approximately 50 Hz. 19.The method of claim 11, further comprising: delivering one or morecardiac therapies using the implantable medical device; and controllingthe delivery of the one or more cardiac therapies using the detectedcardiac electrical events.